Ignorance as a finite resource (or “Data visualization resources”)

I’m not a data visualization professional, nor do I play one on TV. Even though I’ve been working with data professionally for over 20 years[1], I’ve generally been on the back end of systems, working on data platforms and not data visualization. I’ve been known to say on occasion[2] that I’ll make your data sing, but you probably don’t want me responsible for making it pretty. If I’m your report designer, building them will take five times as long, and the reports will suck ten times as much.

Before I joined Microsoft, I worked for many years as a consultant. When working with potential clients, I would often present my ignorance as an asset. This may sound strange, but think about the truth in this simple pitch: “You and your team know too much. There are some questions you will never think to ask, because they’re just too obvious. One of the strengths I will bring to this engagement is my ignorance – I will ask those questions and together we will find answers and build solutions.”

Sometimes ignorance doesn’t feel like an asset – sometimes it just gets in the way. In the past few months this has been the case as I’ve been trying to get build Power BI reports for some of the data I work with day to day. To be more specific, I’ve been trying to build reports that don’t suck. I already have functional reports, but I believe that there are insights waiting in the data that could be discovered and shared more easily if I had stronger data visualization skills. I read documentation, and followed examples and reached out to multiple friends and colleagues or advice and… and often found that not only did I not have the knowledge to effectively visualize my data, I often struggled to effectively communicate my goals. I was both mega-ignorant and meta-ignorant.

Which brings me to the point of this post: I’m hoping to use this monumental ignorance as an asset.

Earlier this week I reached out on Twitter asking for help. I wanted to find resources that could help me build my data visualization skills, and to build my vocabulary of terms and concepts so I could ask better questions. I wanted to address both the mega-ignorance and the meta-ignorance. So I asked both Alberto Cairo[3] and Alyssa Fowers[4] by name, and asked for help in general, and boy did I get it.

Hey @AlbertoCairo and @alyssafowers and all the other amazing #DataViz folks out there – is there a standard resource (or standard vocabulary) for data visualizations and the data attributes they display?

I learned one immediate lesson from the replies to this post: I did not do an effective job in communicating my goals. Previously I had struggled when asking for tactical data visualization help; here I was struggling when asking for strategic help, and most of the responses weren’t even close to what I was asking for[5]. This was frustrating, but it validated my understanding of the problem, and reinforced my belief that I need a deeper understanding of the concepts and nomenclature of data visualization if I’m going to improve.

…which is sort of where I was going with this whole post[7]. Ignorance as a finite resource, remember?

I’ve long observed that when one person is struggling with something, he’s typically not alone. When one person asks a question, a dozen other people breathe a silent sign of relief, because they had the same question but didn’t dare ask it. Working under the assumption that I’m not alone in this starting point, I’m hoping to use my current state of ignorance, and the upcoming process of destroying that ignorance, to start a “data visualization as a second language” series of posts.

If you’re looking for excellent tools that you can use today to build on your existing foundation of data visualization knowledge and skills, click on the Twitter link above because there are over a dozen web sites, books, and other resources – and I’m too lazy to copy them all here. But if you’re interested in joining me on my learning journey, stay tuned until August.

Do you think this type of content has an audience? Are you that audience? I’d love to hear from you…

[1] How young is too young to play the “old man” card so consistently? Asking for a friend.

[2] Typically these are occasions when someone is looking at one of my ugly reports, and I’m feeling self-conscious.

[5] Yes, I know this is how Twitter works. I’m trying to be generous here – work with me.

[6] Click on the “Who is this book for” link and tell me that you don’t wish every technical book had this information so readily available.

[7] Brevity will never be my forte.

[8] I was originally thinking of “Data Viz 101” but that sounded too advanced, and if I went with the second idea of “Data Viz 001” I know I would forever be making “James Bond’s analyst colleague” jokes. DVSL wasn’t my first choice, but I think I like it.

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Good to hear. But….why just buy one book? Why not buy a whole bunch, park them on your bedside table, and make a commitment to get though them? I must have 30 dataviz books already, and at the low price of a book I don’t hesitate in buying more, 5 or so at a time…even if just to find great books to recommend. I’ve got a whole stack of them unread still, including Alberto Cairo’s books. But I’ll get to them…especially if they are just sitting there, guilting me.

Yes, Andy Kirk’s book is great. But there are a whole bunch of other books out there equally great, such as Storytelling with Data by Cole Nussbaumer Knaflic. Or the entire Edward Tufte series. Or Information Dashboard Design, by Stephen Few.

At the moment I’m working my way through Good Charts by Scott Berinito, and loving every page of it. Haven’t got to the middle, but already recommend it on the strength of the intro and brief history of datavis alone.

I’m really glad you are looking further into datavis. One of the biggest requests on the Ideas site is to allow Sparklines in a matrix. These books will help underscore why this is a no brainer for a product that aims to be a BI tool. And hopefully they will help you look at the sample dashboards that MS put out for Power BI with fresh eyes, so you can say “Folks, if we want to convince data viz practitioners that Power BI is a worthy tool, we’re going to have to do better that this”.

You have just touched on topics of my last two blog posts:
– Importance of pursuing ignorance in data science
– When NOT to use data visualization.

While I absolutely agree that ignorance is an asset. I don’t think it is finite. The only way it becomes finite is if you stop asking questions. And that is something a scientist or an analyst just cannot afford to do.

Secondly, I appreciate the importance of data visualization. But lately, with the plug’n chug BI solutions available in the name of being user friendly, it has become the only step in data “analysis”. It’s easier than ever to make things pretty. To make them actionable and insightful…that is exceedingly rare. I will take singing data over pretty pictures anyday.

P.S. Promoting PowerBI as a data visualization tool only, is a disservice to the product.